As use of the Internet has been increasing lately, many people are posting their opinions on the Internet through media such as blogs and wikis. Also, the need to refer to opinion information uploaded by others on the Internet in order to evaluate specific information is increasing.
For example, there are various user opinions ranging from product reviews to movie reviews on the Internet. Such respective user opinions can be used when general users want other users' opinions before purchasing products or seeing movies, and also when marketers, stock traders, etc. want various opinions of general users about respective products or companies. In particular, general users tend to purchase a specific product after seeing other users' reviews.
However, opinions on the Internet are only in individual websites, and thus a user must manually search all the individual websites one by one to use the opinions.
It is difficult for users to search all such websites. Also, it is difficult to effectively search for other users' opinions through a general search because web documents with opinions, web documents with affirmative opinions, web documents with negative opinions, etc. coexist.
To solve this problem, active research on user opinion extraction technology is under way in Korean/international academic worlds. Also, an information search field has been remarkably developed since early 2000, and various techniques have been researched.
However, conventional information search technology merely provides a search service based only on information having a keyword, and cannot provide an advanced search service based on affirmative/negative evaluation content in documents or sentences containing each keyword. Recently, attempts have been made to apply user opinion extraction technology to information search, but the application still remains at a level of merely distinguishing affirmative and negative documents from each other.